MIXED
METHODS9715 – Doctoral Seminar
Notes by M. Larsen
Nov. 28, 2014
‘The Third Methodological Movement’
‘The Third Path’‘A research paradigm whose time has
come.
WHY MIXED METHODS
DESIGN?To provide a more complete picture of the phenomenon under study
To increase data validity
Enable researcher to develop analysis and build on original data
MM research – “can help to clarify the formulation of the research problem and the most appropriate ways in which problems or aspects of problems may be theorised and studied….With multiple methods the researcher has to confront the tensions between different theoretical perspectives while at the same time considering the relationship between the data sets produced by the different methods” (Brannen, 1992, pp. 32-33)
CRITICS OF MIXED
METHODS‘Incompatibility thesis’ - qualitative and
quantitative research paradigms cannot
and should not be mixed
(purists – paradigm wars)
Critics of MM - different research
paradigms embody incompatible
assumptions about the nature of the
world and what is important to know
CHALLENGING THE DIVIDE BETWEEN
QUALITATIVE AND QUANTITATIVE
RESEARCH
Hammersley (1992) “Deconstructing the
qualitative-quantitative divide”
- the distinction between these
methodological paradigms is limited
and dangerous
Presents 7 issues concerning the
quant/qual distinction and challenges
each of them.
1) Qualitative vs quantitative
dataAssumptions:
Qual research - words
Quant – numbers
But… this distinction is problematic
- large proportion of research reports combine both
- ethnographers use words like “Regularly”, Frequently, Often, Sometimes, Generally, Typically
If this is about precision, then precision doesn’t necessarily mean the use of numbers
1) Qualitative vs quantitative data
cont’d.
“We are not faced, then, with a starkchoice between words and numbers, oreven between precise or imprecise data.Furthermore, our decisions about whatlevel of precision is appropriate in relationto any particular claim should depend onthe nature of what we are trying todescribe, on the likely accuracy of ourdescriptions, on our purposes, and on theresources available to us; not onideological commitments to onemethodological paradigm or another.”(p.43)
2) The investigation of natural vs
artificial settingsAssumptions:Quant – artificial setting – experimentalQual – naturalBut…this distinction is spurious What happens in classroom is not necessarily more natural than what goes on in a psych lab“To treat classrooms…as natural and experiments as artificial is to forget that social research is itself part of the social world.” (p. 44)
2) The investigation of natural vs
artificial settingsReactivity – individuals alter their performance or behavior due to the awareness that they are being observed -both quant and qual research can lead to reactivity(Hawthorne effect)
“The terms ‘natural’ and ‘artificial’ havemisleading connotations. And while theissue of ecological validity is important, it isnot the only important methodological issue.Nor does research in ‘natural’ settingsguarantee ecological validity, any more thanresearch in ‘artificial’ settings automaticallydebars us from it.” (p. 45)
3) A focus on meanings rather
than behaviorAssumptions:
Qual research - interpretive (meaning)
Quant research – positivist (behaviours)
But… rare that qual research simply
documents point of view of participants
Researcher is involved in interpretation of
data
Much quant research concerned with attitudes not just behavior
3) A focus on meanings rather
than behavior
“As regards differences in the approachthat attitude researchers andethnographers employ in identifyingattitudes/perspectives, the contrast isbetween the use of attitude scales andmore unstructured approaches…Hereagain, we do not have a clear-cutdistinction between two contrastingapproaches.” (p. 46)
4) Adoption or rejection of natural
science as a modelAssumptions:
Qual – reject natural science as modelQuant –natural science – exemplary
“Not even the most extreme positivistwould argue that the methods of physicsshould be applied lock, stock and barrel tothe study of the social world. And there arefew supporters of qualitative research whowould insist that there is no aspect ofnatural science method that is relevant tosocial research. What is involved here is amatter of degree.” (p. 47)
5) An inductive vs deductive
approachAssumption:
Quant = deductive or hypothetico-deductive
Qual = inductive
But… “Quant research does not always test hypotheses: its goal is often descriptive.” (Brannen, 1992, p. 8) Some quant research is concerned with
theory generationSome qual research is deductiveLots of qual research is simply descriptive
5) An inductive vs a deductive
approachAll research involves induction and deduction to some degree– impossible that researchers not be influenced by prior knowledge
“What is true is that one can distinguishbetween studies that are primarily exploratory,being concerned with generating theoreticalideas, and those which are more concernedwith testing hypotheses. But these types ofresearch are not alternatives; we need both.Nor need the former be quantitative and thelatter qualitative in other senses of thoseterms.” (p. 48)
6) The identification of cultural
patterns as against seeking scientific
lawsAssumption:
Quant –committed to discovery of scientific laws
Qual – committed to identifying cultural patterns
Yet… much quant is concerned with description
Early qual researchers justified their practice by claiming that it produced scientific laws and even today they claim their goal is theory generation
“Thus the distinction between identifying patterns and pursuing laws seems to provide little clear basis for the division between quant and qualitative methods.” (p. 50)
7) Idealism vs realism
Assumption:
Quant – realist epistemology
Qual- idealist
“More important than the empirical question ofwhether it is true that quant researchers arerealists and qual researchers idealists, though, isthe philosophical issue of whether there is anynecessary connection between qual method anda particular epistemological position….historysuggest that there is little reason to believe thatthere is such a connection. And we mustremember that there are many more than 2epistemological positions available.” (p. 51)
METHODOLOGY OF COMBINING
APPROACHES – CONSIDERATIONS
1) Timing - What will the timing of qual
and quant methods be? What will the
order be? Will it be concurrent or
consecutive?
2) Weighting Dimension -What will be
the relative importance, weight or
priority, given to qualitative &
quantitative methods?
Equal
Emphasis on Qualitative or
Quantitative
METHODOLOGY OF COMBINING
APPROACHES – CONSIDERATIONS
cont’d.3) Mixing Dimension - How will qual and quant methods be mixed? How will the 2 data sets be mixed?
Merged
Embedded within one another
Connected in another way
Complementary
Integration
Fundamental Principle of Mixed
Methods Research
Combine the methods in a way that
achieves complementary strengths and
non-overlapping weaknesses (Johnson
& Onwuegbuzie, 2004)
1) Timing
2) Weighting
3) Mixing Dimension
MIXED METHODS DESIGNS
1) Triangulation/ Multiple Methods
Within-method – the same method
being used on different occasions
Between-method – using different
methods in relation to the same topic
Purpose of triangulation – to obtain
complementary quant and qual data on
the same topic
2) Embedded Design
Different research questions require
different types of data to answer them
Complementary – qual and quant data
complement one another
1 or 2 phase
3) Explanatory Design
1st phase – quantitative (e.g. surveys)
2nd phase – qualitative (e.g. classroom
observation)
Qualitative data needed to explain results
1st phase quant – may be used to guide the
selection of 2nd phase in-depth qual study
4) Exploratory Design
1st phase – qualitative
2nd phase – quantitative
Need to develop a measurement instrument
1st phase - get a deeper understanding of the issue/phenomenon
2nd phase - survey to measure its distribution and prevalence.
PRACTICAL ISSUES
1) Politics of research – evidence-based
research - AERA Scientifically Based Research
2) Costs
3) Researchers: skills, careers,
disciplines
4) Social Organization of the Research
Team
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